Measuring Progress and Regress in Printed Media Using Malmquist Productivity Index in Data Envelopment Analysis
Subject Areas : Media Management
Hanieh Haghighinia
1
,
Mohsen RostamyMalkhalifeh
2
,
Mohammad Soltanifar
3
,
Akbar Nasrollahi kasmani
4
1 - دانشجوی دکتری مدیریت رسانه‌ای، واحد علوم و تحقیقات، دانشگاه آزاد اسلامی، تهران، ایران
2 - دانشیار، گروه ریاضی، واحد علوم و تحقیقات، دانشگاه آزاد اسلامی، تهران، ایران
3 - دانشیار گروه علوم ارتباطات اجتماعی، واحد علوم و تحقیقات، دانشگاه آزاد اسلامی، تهران، ایران
4 - استادیار گروه مدیریت رسانه‌ای، واحد تهران مرکزی، دانشگاه آزاد اسلامی، تهران، ایران
Keywords: Printed Media, Performance Measurement, Data envelopment analysis (DEA), Malmquist Productivity index (MPI),
Abstract :
Limitation of resources is an undeniable fact, which is dealt with many organizations such as media organizations. Hence, improving the performance of resource utilization of these organizations is one of the most important concerns of the managers. As a result, a manager must evaluate the performance of their organizations frequently. In this paper, we intend to measure the progress and regress of Iranian printed newspapers between two times 2016 and 2017. The current study is applied in terms of purpose and uses the Malmquist Productivity Index (MPI), which is a very useful approach in Data Envelopment Analysis (DEA) to measure the rate of progress and regress of decision-making units (DMUs) under evaluation. The data analysis was done utilizing GAMS, which is a high-level modeling system for mathematical programming and optimization. After reviewing the performance measurement literature and interviewing with media management specialists and also experts from the Ministry of Culture and Islamic Guidance-Deputy of Press and Information Affairs, appropriate indicators were recognized and selected. The results of the comparison of intra-organizational indicators in two consecutive years of 2016 and 2017 represents that 29 units from 87 DMUs have experienced progress and 58 ones regressed. In order to improve the performance of the regressed units, an appropriate strategy has been proposed.
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Cooper, W.W., Seiford, L.M. & Tone, K. (2007). “Data envelopment analysis: A comprehensive text with models, applications”, references and DEA-solver software, 2nd ed. New York: Springer.
Farzipoor Saen, R. (2011). “Media selection in the presence of flexible factors and imprecise data”, Journal of The Operational Research Society (JORS), Vol. 62, PP. 1695–1703.
Fortunati, L. & O'sullivan, J. (2019). “Situating the social sustainability of print media in a world of digital alternatives”, Telematics and Informatics (T&I), Vol. 37, PP. 137-145.
Goldin, C. (2014). “Human Capital”, Handbook of Clio metrics, Department of economics Harvard university and national bureau of economic research.
Haas, D.A. & Murphy, F.H. (2003). “Compensating for non-homogeneity in decision-making units in data envelopment analysis”, European Journal of Operational Research (EJOR), Vol. 144, PP. 530-544.
Heini, O. (2007). “Performance measurements: Designing a generic measure and performance indicator model”, Department of Information Systems of the University of Geneva, P. 136.
Jafari, Y. (2014). “Malmquist productivity index for multi time periods”, International Journal of Data Envelopment Analysis (IJDEA), Vol. 2, PP. 315-322.
Jantunen, A., Tarkiainen, A., Chari, S. & Oghazi, P. (2018). “Dynamic capabilities, operational changes, and performance outcomes in the media industry”, Journal of Business Research (JBR), Vol. 89, PP. 251-257.
Jiao, H., Alon, I., Koo, C.K. & Cui, Y. (2013). “When should organizational change be implemented? The moderating effect of environmental dynamism between dynamic capabilities and new venture performance”, Journal of Engineering and Technology Management (JET-M), Vol. 30(2), PP. 188-205.
Makkonen, H. Pohjol, M. & Olkkonen, R. (2014). “Dynamic capabilities and firm performance in a financial crisis”, Journal of Business Research (JBR), Vol. 67(1), PP. 2707-2719.
Martinez-Nunez, M. & Perez-Aguiar, W.S. (2014). “Efficiency analysis of information technology and online social networks management: An integrated DEA-Model assessment”, Information & Management (I&M), Vol. 51, PP. 712-725.
Moullin, M. (2007). “Linking performance measurement and organisational excellence”, International Journal of Health Care Quality Assurance (IJHCQA), Vol. 20(3), PP. 181-183.
Neely, A., Gregory, M. & Platts, K. (1995). “Performance measurement system design: A literature review and research agenda”, International Journal of Operations & Production Management (IJOPM), Vol. 25(12), PP. 1228-1263.
Song, Y., Schubert, T., Liu, H. & Yang, G. (2019). “Measuring scientific productivity in China using Malmquist productivity index”, Journal of Data and Information Science (JDIS), Vol. 4(1), PP. 32-59.
Teece. D.J. (2018). “Business models & dynamic capabilities”, Long Range Planning, Vol. 51(1), PP. 40-49.
Wang, Y.M. & Lan, Y.X. (2011). “Measuring Malmquist productivity index: A new approach based on double frontiers data envelopment analysis”, Mathematical and Computer Modelling, Vol. 54, PP. 2760-2771.
Wirtz, B.W. (2011). “Media and internet management”, Wiesbaden, Germany: Gabler Verlag, 2011 edition (July 14, 2011). ISBN-13: 978-3-8349-3010-1 (paperback), P. 569.
Beggs, j. (2018). “Learn About the Production Function in Economics”, Available at: https://www.thoughtco.com/ the-production-function-overview-1146826 [cited 2018 Dec 23].
Majaski, Ch. (2019). “Human Capital vs”, Physical Capital: What's the Difference? Available at: https://www.investopedia.com /ask/answers/062616/human-capital-vs-physical-capital-what-difference.asp [cited 2019 Feb 25].
https://www.goodreads.com/quotes/166961-when-you-can-measure-what-you-are-speaking-about-and